Data compression techniques are commonly used to achieve a low bit rate in the digital representation of signals for efficient processing, transmission, and storage. The size of seismic datasets, for example, continues to increase due to the need of extracting oil from more complex geologies. This drives demand for better sensor acquisition technologies, higher resolution hydrocarbon models, more iterations of analysis cycles, and increased integration of a broader variety of data types. In addition, four-dimensional (4D) modeling techniques have been developed to monitor and simulate reservoirs over time, based on the acquisition of seismic data from the same area at different points in time. Thus, seismic data compression has become important in geophysical applications, for efficient processing, storage and transmission of seismic data. A need therefore exists for improved techniques for compressing both raw and processed seismic data.